Cytokine Activation Reveals Tissue-Imprinted Gene Profiles of Mesenchymal Stromal Cells
Bibliographic record
Abstract
Development of standardized metrics to support manufacturing and regulatory approval of mesenchymal stromal cell (MSC) products is confounded by heterogeneity of MSC populations. Many reports describe fundamental differences between MSCs from various tissues and compare unstimulated and activated counterparts. However, molecular information comparing biological profiles of activated MSCs across different origins and donors is limited. To better understand common and source-specific mechanisms of action, we compared the responses of 3 donor populations each of human umbilical cord (UC) and bone marrow (BM) MSCs to TNF-α, IL-1β or IFN-γ. Transcriptome profiles were analysed by microarray and select secretome profiles were assessed by multiplex immunoassay. Unstimulated (resting) UC and BM-MSCs differentially expressed (DE) 174 genes. Signatures of TNF-α-stimulated BM and UC-MSCs included 45 and 14 new DE genes, respectively, while all but 7 of the initial 174 DE genes were expressed at comparable levels after licensing. After IL-1β activation, only 5 of the 174 DE genes remained significantly different, while 6 new DE genes were identified. IFN-γ elicited a robust transcriptome response from both cell types, yet nearly all differences (171/174) between resting populations were attenuated. Nine DE genes predominantly corresponding to immunogenic cell surface proteins emerged as a BM-MSC signature of IFN-γ activation. Changes in protein synthesis of select analytes correlated modestly with transcript levels. The dynamic responses of licensed MSCs documented herein, which attenuated heterogeneity between unstimulated populations, provide new insight into common and source-imprinted responses to cytokine activation and can inform strategic development of meaningful, standardized assays.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".